Today's utility monitoring systems provide end-users with the capability to alarm on a vast array of anomalous parameters. For example, many electrical system monitoring devices can detect and notify the end-user of overvoltage transient events, voltage sags, excessive voltage unbalance, harmonic distortion issues, etc. Although each of these alarms is beneficial, an end-user's “big picture” understanding of the overall condition of a utility monitoring system may be clouded by the details from so many discrete alarms. The sheer number of discrete alarms can be overwhelming and tend to obfuscate rather than pinpoint the source(s) of the problem by inundating the end-user with redundant information. Furthermore, the end-user may not fully comprehend the impact (or potential impact) of an event as indicated by a discrete alarm within their facility because it can be difficult to determine how the various alarms interrelate with one another.
What is needed, therefore, is an automated data integration technique, including automatic precision alignment of data and automatic hierarchical classification of system layout. The present invention is directed to satisfying this and other needs.